Radiation Leukemia Virus Common Integration at the <i>Kis2</i> Locus: Simultaneous Overexpression of a Novel Noncoding RNA and of the Proximal <i>Phf6</i> Gene
Bibliographic record
Abstract
Retroviral tagging has been used extensively and successfully to identify genes implicated in cancer pathways. In order to find oncogenes implicated in T-cell leukemia, we used the highly leukemogenic radiation leukemia retrovirus VL3 (RadLV/VL3). We applied the inverted PCR technique to isolate and analyze sequences flanking proviral integrations in RadLV/VL3-induced T lymphomas. We found retroviral integrations in c-myc and Pim1 as already reported but we also identified for the first time Notch1 as a RadLV common integration site. More interestingly, we found a new RadLV common integration site that is situated on mouse chromosome X (XA4 region, bp 45091000). This site has also been reported as an SL3-3 and Moloney murine leukemia virus integration site, which strengthens its implication in murine leukemia virus-induced T lymphomas. This locus, named Kis2 (Kaplan Integration Site 2), was found rearranged in 11% of the tumors analyzed. In this article, we report not only the alteration of the Kis2 gene located nearby in response to RadLV integration but also the induction of the expression of Phf6, situated about 250 kbp from the integration site. The Kis2 gene encodes five different alternatively spliced noncoding RNAs and the Phf6 gene codes for a 365-amino-acid protein which contains two plant homology domain fingers, recently implicated in the Börjeson-Forssman-Lehmann syndrome in humans. With the recent release of the mouse genome sequence, high-throughput retroviral tagging emerges as a powerful tool in the quest for oncogenes. It also allows the analysis of large DNA regions surrounding the integration locus.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".